Paper Type
ERF
Abstract
This study conducts a systematic literature review (SLR) to synthesize research at the intersection of information systems (IS), artificial intelligence (AI), and climate adaptation. While AI-driven solutions have demonstrated promise in supporting climate resilience efforts, research in the IS field remains fragmented across diverse domains. Using computational methods for structured search and relevance filtering, we identified 359 academic papers and analyzed them using Non-Negative Matrix Factorization (NMF) topic modeling. Eight key topics emerged, which highlight areas such as climate modeling, disaster resilience, agricultural adaptation, and smart urban planning. Preliminary findings indicate growing academic interest, especially since 2020, and reveal both distinct and interconnected research streams. This review organizes dispersed knowledge, identifies research gaps, and outlines future research directions to advance AI and IS contributions to climate resilience.
Paper Number
2277
Recommended Citation
Yoon, YoungHo; Iddrisu, Mubarak; Lee, Carol; and Bharati, Pratyush, "Information Systems, AI and Climate Resilience: A Systematic Literature Review" (2025). AMCIS 2025 Proceedings. 50.
https://aisel.aisnet.org/amcis2025/intelfuture/intelfuture/50
Information Systems, AI and Climate Resilience: A Systematic Literature Review
This study conducts a systematic literature review (SLR) to synthesize research at the intersection of information systems (IS), artificial intelligence (AI), and climate adaptation. While AI-driven solutions have demonstrated promise in supporting climate resilience efforts, research in the IS field remains fragmented across diverse domains. Using computational methods for structured search and relevance filtering, we identified 359 academic papers and analyzed them using Non-Negative Matrix Factorization (NMF) topic modeling. Eight key topics emerged, which highlight areas such as climate modeling, disaster resilience, agricultural adaptation, and smart urban planning. Preliminary findings indicate growing academic interest, especially since 2020, and reveal both distinct and interconnected research streams. This review organizes dispersed knowledge, identifies research gaps, and outlines future research directions to advance AI and IS contributions to climate resilience.
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